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Motivating sustainability at work: How green pay and rewards influence environmental performance through autonomous motivation

Author

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  • Rashid Ali

    (Indus University)

  • Shahjehan Manthar

    (Higher Education Commission Pakistan)

Abstract

The increasing evidence of climate change and its effects on society call for actions towards sustainable development. One of the instruments for steering sustainable development is the (introduction of) green pay. This paper takes the example of organizations in Karachi, Pakistan, and applied structural equation modelling for exploring the linkages between green compensation and organizational performance. The results suggest that green pay practices are positively associated with sustainable environmental performance. Similarly, autonomous motivations mediate the relationship with organizational environmental performance. The research contributes to the green human resources literature in two ways. First, it applies findings from Western and other contexts to Pakistani organizations. Second, we show that autonomous motivations contribute to the relationship among green compensation, benefits, and corporate environmental performance. The results suggested that green recruitment and selection, green training, green pay, and rewards positively affect autonomous motivation, and that autonomous motivation is positively associated with environmental performance. However, green involvement did not support autonomous motivation. The results indicated that autonomous motivation mediated the effects of green recruitment, selection, training, pay and reward, and environmental performance. Still, no mediating impact of autonomy on the relationship between green involvement and ecological performance was confirmed.

Suggested Citation

  • Rashid Ali & Shahjehan Manthar, 2026. "Motivating sustainability at work: How green pay and rewards influence environmental performance through autonomous motivation," Transformations and Sustainability, Centre for Productivity and Sustainability Analysis, vol. 2(1), pages 65-80.
  • Handle: RePEc:dbj:trasus:v:2:y:2026:i:1:p:65-80
    DOI: 10.63775/jtw9ex10
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